update vllm patch (#13185)

Co-authored-by: gc-fu <guancheng.fu@intel.com>

docker/llm/serving/xpu/docker/vllm_for_multi_arc.patch

@@ -12307,10 +12307,10 @@ index 1b1738f88..2c2ed67b9 100644
              layer_norm_func = RMSNorm if config.rmsnorm else LayerNorm
 diff --git a/vllm/model_executor/models/glm4.py b/vllm/model_executor/models/glm4.py
 new file mode 100644
-index 000000000..8e6e2c11a
+index 000000000..332af5a68
 --- /dev/null
 +++ b/vllm/model_executor/models/glm4.py
-@@ -0,0 +1,318 @@
+@@ -0,0 +1,329 @@
 +# SPDX-License-Identifier: Apache-2.0
 +
 +# Copyright 2025 The Zhipu AI team.
@@ -12339,6 +12339,7 @@ index 000000000..8e6e2c11a
 +import torch
 +from torch import nn
 +from transformers import Glm4Config
++import os
 +
 +from vllm.attention import Attention, AttentionType
 +from vllm.compilation.decorators import support_torch_compile
@@ -12427,7 +12428,6 @@ index 000000000..8e6e2c11a
 +            rope_scaling=rope_scaling,
 +            partial_rotary_factor=partial_rotary_factor,
 +            is_neox_style=False,
-+            dtype=torch.float32,
 +        )
 +        self.attn = Attention(self.num_heads,
 +                              self.head_dim,
@@ -12461,6 +12461,7 @@ index 000000000..8e6e2c11a
 +        prefix: str = "",
 +    ) -> None:
 +        super().__init__()
++        self.config = config
 +        self.hidden_size = config.hidden_size
 +        rope_theta = getattr(config, "rope_theta", 1000000)
 +        rope_scaling = getattr(config, "rope_scaling", None)
@@ -12519,8 +12520,9 @@ index 000000000..8e6e2c11a
 +        # Fully Connected
 +        hidden_states, residual = self.post_attention_layernorm(hidden_states, residual)
 +        hidden_states = self.mlp(hidden_states)
-+        hidden_states = hidden_states.to(torch.float32)
-+        hidden_states = torch.clamp(hidden_states, min=-1e36, max=1e36)
++        if self.config.num_hidden_layers == 61:  # GLM-4-32B-0414
++            hidden_states = hidden_states.to(torch.float32)
++            hidden_states = torch.clamp(hidden_states, min=-1e36, max=1e36)
 +        hidden_states = self.post_mlp_layernorm(hidden_states)
 +
 +        return hidden_states, residual
@@ -12562,6 +12564,15 @@ index 000000000..8e6e2c11a
 +    def __init__(self, *, vllm_config: VllmConfig, prefix: str = ""):
 +        super().__init__()
 +        config = vllm_config.model_config.hf_config
++        if config.num_hidden_layers == 61:  # GLM-4-32B-0414
++            if vllm_config.model_config.dtype != torch.float32:
++                vllm_config.model_config.dtype = torch.float32
++                logger.warning_once("vLLM xpu: GLM-4-32B-0414 model is only supported with FP32. Converting dtype to torch.float32.")
++            sdp_disabled_flag = os.getenv("IPEX_LLM_DISABLE_SDP_CAUSAL", None)
++            if sdp_disabled_flag != "1":
++                logger.warning_once("vLLM xpu: GLM-4-32B-0414 model is currently not supported with sdp_causal(). Setting IPEX_LLM_DISABLE_SDP_CAUSAL=1.")
++                os.environ["IPEX_LLM_DISABLE_SDP_CAUSAL"] = "1"
++
 +        quant_config = vllm_config.quant_config
 +        lora_config = vllm_config.lora_config
 +
@@ -14681,7 +14692,7 @@ index 000000000..bda3de2d3
 +            loaded_params.add(name)
 +        return loaded_params
 diff --git a/vllm/model_executor/models/registry.py b/vllm/model_executor/models/registry.py
-index c0a3c59ba..8614c2273 100644
+index c0a3c59ba..b8f54e82e 100644
 --- a/vllm/model_executor/models/registry.py
 +++ b/vllm/model_executor/models/registry.py
 @@ -57,6 +57,7 @@ _TEXT_GENERATION_MODELS = {
@@ -14709,6 +14720,18 @@ index c0a3c59ba..8614c2273 100644
      "XverseForCausalLM": ("llama", "LlamaForCausalLM"),
      "Zamba2ForCausalLM": ("zamba2", "Zamba2ForCausalLM"),
      # [Encoder-decoder]
+@@ -307,8 +311,9 @@ class _LazyRegisteredModel(_BaseRegisteredModel):
+ 
+     # Performed in another process to avoid initializing CUDA
+     def inspect_model_cls(self) -> _ModelInfo:
+-        return _run_in_subprocess(
+-            lambda: _ModelInfo.from_model_cls(self.load_model_cls()))
++        # return _run_in_subprocess(
++        #     lambda: _ModelInfo.from_model_cls(self.load_model_cls()))
++        return _ModelInfo.from_model_cls(self.load_model_cls())
+ 
+     def load_model_cls(self) -> Type[nn.Module]:
+         mod = importlib.import_module(self.module_name)
 diff --git a/vllm/model_executor/models/roberta.py b/vllm/model_executor/models/roberta.py
 index a09741a55..d989a12fa 100644
 --- a/vllm/model_executor/models/roberta.py